Construction of Saccharomyces cerevisiae strains with ...

ARTICLE

Construction of Saccharomyces cerevisiae StrainsWith Enhanced Ethanol Tolerance by Mutagenesisof the TATA-Binding Protein Gene andIdentification of Novel Genes AssociatedWith Ethanol Tolerance

Jungwoo Yang,1 Ju Yun Bae,1 Young Mi Lee,1 Hyeji Kwon,3 Hye-Yun Moon,4

Hyun Ah Kang,4 Su-bog Yee,1 Wankee Kim,5 Wonja Choi1,2,3

1Microbial Resources Research Center, College of Natural Sciences, Ewha Womans,

University, Seoul, Korea; telephone: þ82-2-3277-2892; fax: þ82 23277 2385;

e-mail: [email protected] of Life Science, College of Natural Sciences, Ewha Womans, University,

Seoul, Korea3Division of Life and Pharmaceutical Sciences, Ewha Womans University, Seoul, Korea4Department of Life Science, College of Natural Sciences, Chung-Ang University,

Seoul, Korea5Institute for Medical Sciences, School of Medicine, Ajou University, Suwon, Korea;

telephone: þ82-31-219-4506; fax: þ82 31 219 4508; e-mail: [email protected]

Received 14 October 2010; revision received 28 February 2011; accepted 7 March 2011

Published online 17 March 2011 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/bit.23141

ABSTRACT: Since elevated ethanol is a major stress duringethanol fermentation, yeast strains tolerant to ethanol arehighly desirable for the industrial scale ethanol production.A technology called global transcriptional machinery engi-neering (gTME), which exploits a mutant library of SPT15encoding the TATA-binding protein of Saccharomyces cer-evisiae (Alper et al., 2006; Science 314: 1565–1568), seems toa powerful tool for creating ethanol-tolerant strains. How-ever, the ability of created strains to tolerate high ethanol onrich media remains unproven. In this study, a similarstrategy was used to obtain five strains with enhancedethanol tolerance (ETS1–5) of S. cerevisiae. Comparingglobal transcriptional profiles of two selected strains ETS2and ETS3 with that of the control identified 42 genes thatwere commonly regulated with twofold change. Out of 34deletion mutants available from a gene knockout library, 18were ethanol sensitive, suggesting that these genes wereclosely associated with ethanol tolerance. Eight of themwere novel with most being functionally unknown. Toestablish a basis for future industrial applications, strainsiETS2 and iETS3 were created by integrating the SPT15mutant alleles of ETS2 and ETS3 into the chromosomes,which also exhibited enhanced ethanol tolerance and survi-

val upon ethanol shock on a rich medium. Fermentationwith 20% glucose for 24 h in a bioreactor revealed that iETS2and iETS3 grew better and produced approximately 25%more ethanol than a control strain. The ethanol yield andproductivity were also substantially enhanced: 0.31 g/g and2.6 g/L/h, respectively, for control and 0.39 g/g and 3.2 g/L/h,respectively, for iETS2 and iETS3. Thus, our study demon-strates the utility of gTME in generating strains withenhanced ethanol tolerance that resulted in increase ofethanol production. Strains with enhanced tolerance toother stresses such as heat, fermentation inhibitors, osmoticpressure, and so on, may be further created by using gTME.

Biotechnol. Bioeng. 2011;108: 1776–1787.

� 2011 Wiley Periodicals, Inc.

KEYWORDS: ethanol stress; SPT15; mutagenesis; ethanoltolerance; DNA microarray

Introduction

During ethanol production, ethanol-producing microor-ganisms confront multiple stresses such as high initialsubstrate concentration, increased ethanol concentration,and accumulation of toxic byproducts. In addition to rapidgrowth and efficient fermentation capacity, the ability totolerate these stresses is an important factor in choosing an

Correspondence to: W. Choi and W. Kim

Contract grant sponsor: Korea Ministry of Education, Science and Technology

Contract grant number: 2009-0081512; 2007-2005047

Additional Supporting Information may be found in the online version of this article.

1776 Biotechnology and Bioengineering, Vol. 108, No. 8, August, 2011 � 2011 Wiley Periodicals, Inc.

ethanol producer (Ding et al., 2009; Gibson et al., 2007;Zhao and Bai, 2009). Saccharomyces cerevisiae has been usedas a primary microorganism for ethanol production on anindustrial scale. The accumulation of ethanol to toxicconcentrations during fermentation is the major stress thatcauses reduced ethanol production and eventual stuckfermentations (Gibson et al., 2007). Thus, the developmentof S. cerevisiae strains that can endure ethanol stress is bothprudent and important. One way to address such an issue isto understand the mechanisms underlying ethanol stresstolerance. For this, two different molecular approacheshave recently been used to identify genes involved inethanol tolerance: genome-wide DNA microarray analysis(Alexandre et al., 2001; Chandler et al., 2004; Dinh et al.,2009; Hirasawa et al., 2007; Marks et al., 2008; Rossignolet al., 2003; Varela et al., 2005;Wu et al., 2006) and screeningof single gene knockout (SGKO) libraries (Fujita et al., 2006;Kubota et al., 2004; Yazawa et al., 2007; Teixeira et al., 2009;van Voorst et al., 2006; Yoshikawa et al., 2009). However, theissue with these two approaches is that a huge numberof target genes have been identified, representing as much as5–10% of genes encoded in the yeast genome and that fewsuccessful examples have been documented (Hirasawa et al.,2007; Yazawa et al., 2007).

An alternative approach to develop ethanol-tolerantstrains (ETSs) is global transcriptional machinery engineer-ing (gTME). This approach was first used to create a strainwith enhanced ethanol tolerance by generating mutations ofTATA-binding protein encoded by SPT15, which couldgrow at a formerly lethal ethanol concentration (Alper et al.,2006). However, other authors reported that this enhancedethanol tolerance was not reproduced on a rich medium(Baerends et al., 2009), which is not optional for industrialapplications.

Nevertheless, SPT15 mutations altered the transcriptionprofile (Alper et al., 2006). In addition, SPT15 mutationswere pleiotropic (Eisenmann et al., 1989) and somemutations in the regulatory domain of SPT15 resulted intranscriptional increase (Cang et al., 1999). These observa-tions indicate that different mutations of SPT15may induceexpression of different sets of genes. It was of our concernwhether point mutations different those introduced byAlper et al. (2006) could enhance ethanol tolerance on arich medium. In this study, five ETSs containing differentSPT15 mutant alleles were obtained and the effect ofSPT15 mutations on ethanol production was examined,re-empathizing the usefulness of gTME as a tool for creatingstrains tolerant to ethanol and hopefully to other variousstresses.

Materials and Methods

Yeast Strains and Media

S. cerevisiae L3262 (MAT-a; ura3-52 leu2-3,112 his4-34) andBY4741 (MATa his3D1 leu2D0 met15D0 ura3D0) were

used as transformation recipients. The non-essential haploidS. cerevisiae deletion library was used for the verification ofidentified genes. Unless otherwise mentioned, yeast cellswere grown at 308C in YPD (1% yeast extract, 2% peptone,2% glucose, and 1.5% agar for solid plates) for non-selectivepropagation or yeast synthetic complete (YSCD) medium(0.67% yeast nitrogen base without amino acids, amino acidsupplement mixture, 2% dextrose, and 1.5% noble agar forsolid plates) for selective propagation.

Molecular Methods

Plasmid preparation, cloning, and sequencing were per-formed as previously described (Sambrook and Russell,2001). Escherichia coli strain DH5a was used as a host forplasmid preparation.

Reverse Transcription–Polymerase Chain Reaction(RT–PCR) and PCR

For RT, total RNAwas prepared from exponentially growingcells. First strand cDNAs were synthesized by transcribing2mg of total RNAs with random hexamers and 200U ofM-MuLV reverse transcriptase (Promega, Madison, WI)as recommended by the manufacturer. Oligonucleotidesused for PCR are listed in Supplementary Table I. Theamplification conditions were 958C for 1min, 55–608Cfor 1min, and 728C for the appropriate period of timedepending on the length of DNA to be amplified for20 cycles for RT-PCR and 30 cycles for regular PCR. Ifnecessary, PCR products were purified by gel elution, clonedinto the pGEM-T easy vector (Promega), and sequenced.

SPT15 Mutant Library Construction

The open reading frame (ORF) of SPT15wt was PCR-amplified from genomic DNA as a template with primersSPT15ORF-S and SPT15ORF-AS and cloned into thepGEMT-easy vector (Promega), yielding pT-SPT15. TheSPT15 mutant library was generated by using theGeneMorph II random mutagenesis kit (Stratagene, LaJolla, CA) with pT-SPT15 as template and using theaforementioned primers. PCR products were digested withBamHI and EcoRI, and cloned into a pRS316-derivedplasmid, pRS316-GCYH2gR, in which cloned genes areplaced under control of glyceraldehyde-3-phosphate dehy-drogenase promoter (TDH3P) and galactose-1-phosphateuridyl transferase terminator (GAL7T). The resultingplasmids were transformed into E. coliDH5a and incubatedat 308C (to prevent outgrowth of fast-growing cells) togenerate a primary library for SPT15 mutants with totalcolony number being 4� 106. From the sequencing of 20randomly selected colonies, the molecule-based mutationrate was determined to be 70%. Mutations were found atmore than one site, mostly 3–5, in 14 colonies, with theremainder being the wild type. One of these wild-type

Yang et al.: Enhanced Ethanol Tolerance of S. cerevisiae 1777

Biotechnology and Bioengineering

plasmids was used as the control vector (pSPT15wt).Following amplification and large-scale preparation, thelibrary plasmids (500mg) were transformed into S. cerevisiaeL3262 and incubated at 258C (to prevent outgrowth of fast-growing cells) on solid YSCD–Ura. The total number ofyeast colonies was approximately 5� 106 with a transfor-mation efficiency of approximately 1� 104 colony formingunits (CFU)/mg DNA. All the colonies were harvested byscrubbing the surfaces of plates with 15mL YSCD–Ura toprepare a yeast library for SPT15 mutants. After fourfoldpropagation in cell number at 258C, aliquots of the cellsuspension were stored at �808C in the presence of 20%glycerol until used.

Yeast Transformation

All plasmids for yeast transformation were manuallyprepared without RNA digestion. The DNA concentrationwas roughly measured by comparing the band intensity withthat of control DNA of known concentration. This mixtureof DNAs and RNAs was used for yeast transformation aspreviously described (Gietz and Woods, 2002).

Spot Assay and Ethanol Susceptibility Assay

For spot assay, aliquots (5ml) of cells grown to an opticaldensity at 600 nm (OD600) of 1.0 were tenfold serially dilutedand spotted onto solid synthetic or rich media containingappropriate concentrations of ethanol. Plates were incu-bated at 308C for 4–6 days.

For ethanol susceptibility assay, Cells grown to OD600 of1.0 were harvested, equally divided into fresh YSCD–Uramedia containing 12.5% and 15% ethanol (v/v), andincubated at 308C for 4–6 h. At appropriate time points,aliquots were properly diluted and plated onto solid YPD.Cell viability was measured as a function of time andexpressed as the relative number of CFU.

Transcriptome Profiling and Data Analysis

S. cerevisiae 30K oligomicroarrays (MYcroarray, Ann Arbor,MI) were used for transcriptome profiling. Total RNA wasprepared from exponentially growing cells and RNA qualitycontrol for microarray analysis were performed as describedpreviously (Park et al., 2007). cDNAs incorporated withaminoallyl-dUTP were synthesized from 40 to 50mg oftotal RNA using an Aminoallyl post DNA Labeling kit(GeneChem, Daejeon, Korea) and a superscript reversetranscriptase (Invitrogen, Carlsbad, CA). The synthesizedcDNA was labeled with NHS-ester Cy dyes and used forhybridization. Hybridized slides were washed by SSC buffer,and then scanned with a ScanArray 5000 scanner (Hewlett-Packard, Palo Alto, CA). Rawmicroarray data were analyzedby using ArrayNorm (http://genome.tugraz.at/), a platform-independent Java tool for normalization and statisticalanalysis (Pieler et al., 2004). Clustering for genes with

the average change higher than twofold was carried outusing Cluster 3.0 (http://rana.lbl.gov/EisenSoftware.htm).Enrichment of functional categories among differentiallyexpressed genes was analyzed using the MIPS FunctionalCatalogue (http://mips.gsf.de). Specific gene functions werebased on the Saccharomyces Genome Database (http://www.yeastgenome.org), and transcription factor-bindingsties were analyzed by YEASTRACT (http://www.yeastract.com/index.php). To validate DNA microarray data, semi-quantitative reverse transcription PCR was performed asdescribed previously (Oh et al., 2004) with the RNA samplesused for microarray experiments.

Genomic Integration

The DNA fragments covering the TDH3p, ORF, and GAL3Twere excised from pSPT15wt, pSPT15-M2, and pSPT15-M3and cloned into the integrating vector pRS406. The resultingplasmids were linearized with ApaI and transformed into S.cerevisiae L3262. Genomic integration was verified by PCRwith primer sets shown in Supplementary Table 1.

Fermentation

Ethanolic fermentations were performed at 308C with cellsinitially adjusted to an OD600 of�1.0 in 500mL YPD20 (2%peptone, 1% yeast extract, 0.02% (NH4)2SO4, and 20%glucose) in 1-L bioreactor with pH maintained at 5.5 andoxygen supplied at 200mL/min. The cultures were agitated at400 rpm with antifoaming agent added. Samples werecollected at appropriate time points and analyzed for con-centration of glucose, ethanol, and glycerol produced duringfermentation by performing high-pressure liquid chromato-graphy (HPLC). The samples were loaded onto Aminex HPX-87H column (Bio-Rad, Hercules, CA) set to 608C and elutedwith 0.5mM H2SO4 at a constant flow rate of 0.6mL/min.Peaks were detected by a refractive index detector andquantified according to a calibration curve for each of glucose,ethanol, and glycerol molecules. Cell growth was monitoredby measuring the OD600 with appropriate dilutions.

Results

Identification of Ethanol-Tolerant Strains

To obtain ETSs by screening of a yeast SPT15mutant libraryconstructed in the present study, 5� 106 colony formingunits were spread on the solid YSCD–Ura mediumsupplemented with 12.5% ethanol and incubated at 308C.Seven days after, 15 colonies had developed in the presenceof 12.5% ethanol. The ethanol tolerance of the 15 colonieswas examined by a spot assay on the solid YSCD–Uramedium containing up to 15% ethanol. As a result, five ETSs(ETS1–5) were obtained. All five strains tolerated 15%ethanol, whereas the control did not tolerate ethanolconcentrations exceeding 10% (Fig. 1).

1778 Biotechnology and Bioengineering, Vol. 108, No. 8, August, 2011

To confirm whether the enhanced ethanol tolerance wasconferred by the presence of a mutated SPT15, plasmidswere recovered from ETS1–5 (pSPT15-M1, -M2, -M3, -M4,and -M5, respectively). Sequencing of each SPT15 allele-located mutations in the SPT15 ORF: K201N, G216S, andN225Stop in SPT15-M1; L76V and L175S in SPT15-M2;S42N, C78R, S163P, and I212N in SPT15-M3; F10S andM197K in SPT15-M4; K15T, W26C, and G192D in SPT15-M5 (Fig. 2). A silent mutation (N225Stop) in SPT15-M1yielded a truncated version with 16 residues deleted at the C-terminus. No particular point mutation was common,although one or two residues were changed in the repeatelement 2 of all alleles. This element contains the domaininteracting with Spt3p (amino acid residues 172–179),which has been implicated in the regulation of genetranscription (Alper et al., 2006; Cang et al., 1999). Overall,these data were consistent with the suggestion that themutation of several subregions of Spt15p confers ethanol

tolerance, presumably through the interaction with othercomponents of the transcriptional machinery in addition toSpt3p (Eisenmann et al., 1989).

Each plasmid was re-introduced into L3262 and BY4741to yield rL-ETS1–5 and rBY-ETS1–5. pRS316-GCYH2gRcontaining wild-type SPT15 (SPT15wt) was transformedinto L3262 and BY4741, yielding control strains C-L3262and C-BY4741. When spot-assayed on a synthetic medium,rL-ETS1–5 showed the same degree of ethanol tolerance asETS1–5 did (Fig. 3, top panel). Meanwhile, rBY-ETS1–5showed tolerance to as high as 17.5% ethanol (Fig. 3, bottompanel). This was not surprising, since BY4741 originallydisplayed higher ethanol tolerance than L3262 (data notshown). Thus, the enhanced ethanol tolerance of ETS1–5was suggested to be the effect of mutated SPT15.

Based on the above spot assay results in which ETS2 andETS3 were slightly more tolerant than the remainder, thesetwo were chosen for DNA microarray, testing the ability to

Figure 1. Enhanced ethanol tolerance of ETS1-5. Cells were grown to an OD600 of 1.0 in the YSCD–Ura or YPD liquid media and tenfold serially diluted. Aliquots (5ml) were

spotted onto YSCD–Ura or YPD plates containing appropriate concentrations of ethanol and incubated at 308C for 4–6 days. Control stain (C-L3262) was constructed by

transformation of pSPT15wt into L3262.

Figure 2. Schematic representation of mutated SPT15 alleles. Plasmids (pSPT15-M1–5) were recovered from ETS1–5 and sequenced. Comparison of the deduced amino acid

sequence with SPT15wt locates the position of point mutations (arrows). The map of structural domains is based on the previously published literature (Alper et al., 2006).



grow on a rich medium, and genome integration of SPT15alleles.

Transcriptome Profile Analysis of Ethanol-TolerantMutant Strains

We were interested in genes responsible for enhancedethanol tolerance of ETS2 and ETS3, the expression levelsof which were regulated by SPT15 mutations. To obtainthis information, DNA microarrays for transcriptionalprofiling were conducted with total RNAs prepared fromcontrol C-L3262, ETS2, and ETS3 cells grown to early-logphase in YSCD-Ura. After performing microarray experi-ments in duplicate, expression fold changes were averaged.The raw data have been registered at Gene ExpressionOmnibus under the accession number GSE23965. The levelof SPT15 increased eightfold on average in both ETS2 andETS3 (data not shown). Clustering of genes with fold changehigher than two compared to control displayed differentialexpression patterns between ETS2 and ETS3, reflectingthe effect of different mutations of SPT15 on the globaltranscription (Fig. 4A). To validate the microarray data, theactual expression levels of HSP30, HSP42, and HSP104 wereexamined by RT-PCR. According to the microarray data,

HSP30,HSP42, andHSP104 were up-regulated by 5.7-, 4.3-,and 1.7-fold in ETS2 and 6.3-, 4.1-, and 1.8-fold in ETS3,respectively. The fold increases of those genes wereconsistent with the RT-PCR data (Fig. 4B).

In ETS2, 45 and 11 genes were up- and down-regulated,respectively, whereas in ETS3, 79 and 21 genes were up- anddown-regulated, respectively (Fig. 4C). Thirty-four up-regulated and eight down-regulated genes were sharedbetween ETS2 and ETS3 (Fig. 4C). To gain furtherinformation on the transcriptional regulation of commonlyup- and down-regulated genes, we examined the presence ofputative binding sites for transcription factors presumed tobe involved in various stress responses, such as Msn2p/Msn4p for general stress (Watanabe et al., 2007), Hac1p forprotein secretion stress (Ogawa and Mori, 2004), Hsf1p forheat stress (Yamamoto et al., 2008), and Yap1p for oxidativestress (He and Fassler, 2005). Quite intriguingly, the bindingsites for these transcription factors were highly enriched inthe upstream regions of commonly up-regulated genes(Table I). Particularly, the binding sites for Msn2p/Msn4pwere found in nearly all of commonly up-regulated genes.Meanwhile, the binding sites for Msn4p/Msn2p and Yap1pwere found far less frequently, in contrast to similarfrequencies for Hac1p and Hsf1p, in the eight commonlydown-regulated genes. The collective data suggests that

Figure 3. Confirmation of enhanced ethanol tolerance. Plasmids pSPT15-M1–5 were re-transformed into L3262 and BY4741, yielding rL-ETS1–5 and rBY-ETS1–5, respectively.

Control stain C-BY4741 was constructed by transformation of pSPT15wt into and BY4741. Spot assay was performed as in Figure 1.


Msn4p/Msn2p and Yap1p may be responsible for theregulation of genes associated with ethanol tolerance.

Effect of Commonly Regulated Genes on EthanolTolerance

Of concern was whether the 34 commonly up-regulated andeight commonly down-regulated genes were a cause or aneffect of ethanol tolerance. If the up-regulation of a gene-enhanced ethanol tolerance, it would be highly likely that itsdeletion would render cells sensitive to ethanol. The reversewould be the case for the down-regulated genes. Deletionmutants corresponding to 30 up- and 6 down-regulatedgenes were retrieved from the BY4741 SGKO collection.Those corresponding to four up-regulated genes (YER053C-A, YNR034W-A, YPR145C-A, YBL029C-A) and two down-regulated genes (RRN7 and YOR387C) were not available,probably due to their lethality. BY4741 as control andindividual deletion mutants grown to an OD600 of 0.5 werediluted tenfold and spotted on solid YPD mediumcontaining several different concentrations of ethanol.

The results for 30 deletion mutants corresponding tocommonly up-regulated genes are shown in Figure 4D.Some deletion mutants were sensitive to as low as 6%, farbelow the concentration that exerts toxic effect to BY4741.It was natural that total number of sensitive mutantsincreased as the ethanol concentration increased up to 12%.Sensitivity to 6% ethanol corresponded to deletions inGPH1, SOL4, and SSA4. An additional seven mutants(ALD3, BTN2, SPI1, OM45, RTC3, USV1, and YFR017C)

were sensitive to 8% ethanol. The HSP12 deletion mutantwas sensitive to 10% ethanol. Finally, deletions in HSP30,CTT1, STF2, AIM17, FMP16, RGI1, and PHM8 renderedmutants sensitive to 12% ethanol. Thus, deletion of 18 out of30 genes commonly up-regulated in ETS2 and ETS3conferred ethanol sensitivity. Of these, eight genes (ALD3,BTN2, OM45, RTC3, USV1, YFR017C, FMP16, and PHM8)have never been reported in association with ethanoltolerance or induction upon ethanol shock. Since thesegenes were identified by combination of DNA microarrayand deletion assays, the probability that these genes areinvolved in the enhanced ethanol tolerance is higher thanthose identified by either assay. Meanwhile, none of sixdeletion mutants corresponding to commonly down-regulated genes displayed enhanced growth (data notshown), contrary to our expectation that some of themwould display higher degree of ethanol tolerance than thecontrol.

Construction of Genome-Integrated Strains

As shown above, episomal overexpression of mutated SPT15conferred enhanced ethanol tolerance to cells grown on asynthetic medium. To extend these results to the develop-ment of industrial strains, of great concern was whether ornot the enhanced ethanol tolerance was sustained in bothcells grown on a rich medium and cells with mutated SPT15alleles integrated into the genome. It has been argued thatlow leucine supplementation, but not mutated SPT15, led toenhanced ethanol tolerance (Baerends et al., 2009). More

Figure 4. Microarray data analysis of ETS2 and ETS3. Microarray analysis was performed with Polyþ (A). RNAs prepared from C-L3262 (control), ETS2, and ETS3 grown to

mid-log phase without ethanol stress challenge. Differentially expressed genes with expression fold change >2 were profiled for clustering; I, down-regulated genes, II, up-

regulated genes. B: Microarray data were validated by semi-quantitative RT-PCR of Hsp30, Hsp42, and Hsp104. Numerals 1 and 2 indicate independent duplicates. C: control (L3262)

(C) Venn diagram of up- and down-regulated genes in ETS2 and ETS3. D: Ethanol sensitivity of SGKO mutants. Individual clones corresponding to 30 commonly up-regulated in ETS2

and ETS3 were retrieved from the BY4741 SGKO library. Spot assay was performed as in Figure 1. The parental strain BY4741 was used as a control. Cells were cultured in liquid YPD

and spotted on solid YPD containing 0%, 6%, 8%, 10%, and 12% ethanol, and incubated at 308C for 1–6 days. [Color figure can be seen in the online version of this article, available athttp://wileyonlinelibrary.com/bit]



Table I. Genes commonly regulated in ethanol-tolerant strains ETS2 and ETS3 under no ethanol stress.

Gene

Fold change (2n) Number of binding sites for

ETS2 ETS3

Msn4p/Msn2p Yap1p Hsf1p Hac1pExp1 Exp2 Exp1 Exp2

Up-regulated

Stress response and protein folding

APJ1 1.4 1.1 1.3 1.3 3 0 2 2

ALD3 2.5 1.8 1.6 2.1 2 1 0 1

CTT1 1.7 1.7 1.4 1.9 4 2 4 1

HSP12 1.1 1.5 1.0 1.5 7 0 1 4

HSP30 2.7 2.3 3.0 2.3 0 2 0 0

HSP31 1.5 1.6 4.5 1.5 1 1 2 0

HSP42 2.3 1.9 1.8 2.3 3 0 2 1

SDP1 2.0 1.3 1.8 1.6 3 0 2 0

SSA4 1.0 1.7 1.4 1.0 3 1 1 1

TSL1 1.2 1.2 1.1 1.9 7 0 1 2

YJL144W 3.7 2.3 3.4 2.7 1 1 2 2

Pentose-phosphate pathway

PGM2 1.7 1.2 1.7 2.1 7 1 0 1

SOL4 1.9 1.5 1.6 1.9 1 0 6 0

Cell wall

SPI1 2.0 1.3 1.8 1.6 3 1 2 1

OSW2 1.2 1.0 1.9 1.4 0 1 2 1

Transport

PIC2 1.5 1.1 1.4 1.1 1 0 2 0

BTN2 2.9 3.1 2.9 3.5 2 0 1 0

Metabolism of energy reserves

GPH1 1.1 1.3 1.2 2.1 3 1 0 1

Energy generation

STF2 1.7 1.2 1.8 1.4 2 1 1 2

Unclassified proteins

AIM17 2.4 1.0 1.8 1.9 3 0 2 2

FMP16 1.2 1.3 1.0 1.6 1 1 0 0

OM45 1.4 1.0 1.0 1.5 3 1 4 3

PHM8 1.5 1.6 1.6 1.0 4 0 2 0

RTC3 2.4 2.1 2.1 2.6 4 1 0 0

RTN2 3.4 1.7 1.6 1.4 1 0 2 0

USV1 2.4 1.0 1.8 1.7 6 1 0 0

RGI1 3.3 1.1 3.1 2.2 4 1 4 3

YBL029C-A 1.3 1.0 1.3 1.1 4 1 0 0

YBR285W 1.7 1.2 1.6 1.3 2 1 2 1

YER053C-A 1.3 1.1 1.3 1.0 2 0 0 0

YFR017C 3.1 1.1 2.6 3.6 2 0 0 1

YJR096W 1.4 1.3 1.7 1.6 1 1 2 1

YNR034W-A 3.4 2.5 3.3 3.1 5 1 0 0

YPR145C-A 1.3 1.0 1.6 1.0 0 0 0 0

Down-regulated

Budding cell polarity and filament formation

RAX2 �1.3 �1.0 �1.0 �1.5 0 1 2 0

C-Compound and Carbohydrate Metabolism

BSC1 �2.1 �2.1 �1.5 �2.2 3 1 1 0

Mating (fertilization)

PRM7 �1.0 �1.0 �1.3 �1.2 0 0 0 2

Protein targeting sorting and translocation

VTS1 �1.5 �1.1 �1.1 �1.1 2 0 2 0

rRNA synthesis

RRN7 �1.7 �1.3 �4.0 �1.2 2 0 2 2

Unclassified

VEL1 �2.6 �1.0 �1.2 �5.1 0 0 2 0

YGR035C �1.8 �1.1 �1.1 �1.7 0 0 2 1

YOR387C �2.4 �1.0 �1.1 �4.5 0 0 2 1

Genes showing more than twofold change are listed. Genes whose deletion renders cells sensitive to ethanol are in bold (Fig. 4). Of these, genes that havenever been reported are underlined.


significantly, ethanol tolerance was abolished when cellswere cultured in the YPD-rich medium, which is notoptional for industrial applications. Since ETS2 and ETS3are leucine auxotrophs, the enhanced ethanol tolerance ofthese strains might not be due to mutations in SPT15.However, ETS2 and ETS3 sustained ethanol tolerance onYPD as shown in Figure 5A.

The cell–cell heterogeneity in expression is one of issuesencountered when the information obtained from episomaloverexpression in laboratory strains is scaled up to industrialapplications. Heterogeneity is caused by the inability tocontrol copy number in spite of the continual presence ofselection pressure, which clearly is not optional for yeastculture on an industrial scale. Accordingly, stable expressionand maintenance of the gene in the absence of selectivepressure (i.e., integration into the chromosome) isfrequently desirable. Here, we constructed strains in whichSPT15-M2 and -M3 were integrated into the genome ofL3262; the corresponding constructs were named iETS2 and

iETS3, respectively. The control strain iL3262 were createdwith a plasmid containing SPT15wt. Figure 5B shows thatiETS2 and iETS3 displayed enhanced ethanol tolerance onYPD.

To confirm the spot assay results, the susceptibility to12.5% and 15% ethanol was examined for iETS2 and iETS3(Fig. 5C). At 12.5% ethanol, the timepoint showing 50%viability (T50) was 4.5 h for iETS2 and iETS3, in contrast to3.5 h for the control. A sharper contrast was observed at 15%ethanol, with a T50 of 100min for both iETS2 and iETS3, and40min for control. Thus, we obtained two integrated strainswith enhanced ethanol tolerance on a rich medium.

The Effect of Mutated SPT15s on Ethanol Production

Our next concern was to investigate the relevance ofenhanced ethanol resistance of iETS2 and iETS3 (comparedto control iL3263) to improvement of ethanol production

Figure 5. Ethanol tolerance of episomal and integrated ETS2 and ETS3 on YPD. A: Spot assay of ETS2 and ETS3 on the YPD plate. B: The parental plasmid and plasmids

recovered from ETS2 and ETS3 were integrated into the genome of L3262, yielding iL3262, iETS2, and iETS3, respectively. The spot assay was performed on the YSCD–Ura (top panel)

and YPD plates (bottom panel). C: Ethanol susceptibility of iETS3 and iETS3. Following ethanol shock for the indicated times, iL3262 (*), iETS2 (&), and iETS3 (~) were grown on the

YSCD-Ura plate in the presence of 12.5% and 15% ethanol for 4–6 h. Relative viability was expressed as percentage after counting the number of colony. Experiments were done

in triplicate.



under a certain condition. During the 24-h-long ethanolicfermentations performed in YPD20 media as described inMaterials and Methods section, the cell growth and ethanolproductivity of iL3262 (control), iETS2, and iETS3 wereexamined (Fig. 6). Three strains grew at the same rate until4 h timepoint (Fig. 6A), at which the ethanol concentrationin the medium was below 1% (Fig. 6B), and then iETS2 andiETS3 grew faster than control, indicating that such lowconcentration of ethanol started to affect the cell growth.The growth of control seemed to cease at 16 h timepoint

where the ethanol concentration was 5.8%, while iETS2 andiETS3 continued to grow for 4 h or longer, yieldingsignificant differences in OD600. At 24 h timepoint whereglucose added was almost completely consumed, the finalamounts of ethanol were 77 g/L for both iETS2 and iETS3and 61.5 g/L for control. The ethanol yield for iETS2 andiETS3 (0.39 g/g) was increased by 26% from 0.31 g/g forcontrol. The low ethanol yield by control might be due to thestrain specificity. The ethanol productivity of iETS2 andiETS3 was substantially enhanced by 23% (from 2.6 to 3.2 g/L/h), although the specific ethanol productivity (g ethanol/gcell/h) of the control strain was higher than iETS2 and iETS3due to much less growth of control (�10 OD600) comparedwith iETS2 and iETS3 (�20 OD600, Fig. 6A). The lessethanol production in spite of higher specific ethanolproductivity of control was presumed to result from thecease of cell growth at 16 h timepoint, where the ethanolconcentration was approximately 5.8% (Fig. 6B). The lesscell mass and lower ethanol yield by control duringfermentation seem to be attributed at least in part torelatively higher conversion of glucose to glycerol startingfrom 12 h time point at which the ethanol concentration wasapproximately 3.5% (Fig. 6C). These data together suggestthat the ethanol concentration of as low as 1% negativelyaffects the cell growth and 3.5% ethanol is enough to changethe glucose metabolism in iL3262, and further that iETS2and iETS3 overcome these adversities in favor of efficientethanol production by the enhanced ethanol toleranceconferred by mutated SPT15 alleles.

Discussion

The development of ethanol-tolerant S. cerevisiae strains isof great economic value for brewing and beverage industries,and the manufacture of bioethanol. The organism-basedtraditional approaches, such as evolutionary adaptation,random chemical mutagenesis, and gene shuffling, haveshed little light on the understanding of the molecularmechanisms of ethanol tolerance. Over the past decade,DNA microarray and SGKO library screening have beenextensively exploited to identify genes that are presumed tobe associated with ethanol tolerance. Still, the mechanism ofethanol tolerance remains largely unknown. In the mean-time, several ethanol strains have been developed by genemanipulations, including a few successful cases based on thedata from DNA microarray (Hirasawa et al., 2007) andSGKO library screening (Yazawa et al., 2007), andoverexpression of sonicated genomic fragments (Honget al., 2010). Several strategies identified 18 autologous andtwo heterologous genes whose deletion, disruption, deple-tion, or overexpression to the parental cells (SupplementaryTable 2). In the present study, 18 genes whose up-regulationis very likely to confer ethanol tolerance were identified bythe combined use of DNA microarray and SGKO libraryfrom two ETSs constructed by overexpression of twodifferent SPT15mutant alleles SPT15-M2 and -M3 (Fig. 4A).

Figure 6. Fermentation kinetics of engineered strains. Overnight yeast cells of

control iL3262 (circle) and two ethanol-tolerant strains, iETS2 (square) and iETS3

(triangle), were harvested and transferred to a 1-L bioreactor containing 500mL of

YPD20 (2% peptone, 1% yeast extract, 0.02% (NH4)2SO4, and 20% glucose) with the

initial cell density adjusted to OD600 of 1.0. Ethanolic fermentations were performed as

described in Materials and Methods section. Samples were taken at 4 h intervals to

measure the optical density for cell growth (A) and to determine the concentrations of

glucose (B, open), ethanol (B, closed), and glycerol (C) by using HPLC. Experiments

were done in triplicate.


Intriguingly, none of the autologous genes conferringtolerance by overexpression overlapped with the 18 genes,suggesting that the ethanol tolerance associated with thosegenes is independent of that resulting from the over-expression of both SPT15-M2 and -M3.

Prior to the advent of the DNAmicroarray, the DNA filterarray analysis identified six genes (GPD1, CTT1, HSP12,SpI1, TPS1, and TPS2) up-regulated in an ethanol-tolerantsake strain compared to the parental strain cultivated freefrom ethanol stress (Ogawa et al., 2000). Since then, DNAmicroarray, which has identified a large number ofcandidate genes associated with ethanol tolerance bycomparing the expression profiles of controls (C) and thesame cells challenged with ethanol (e-C) under variedconditions. A recent elaborate study (Ma and Liu, 2010a,b)compared the quantitative transcription dynamics of 175selected genes presumed to be related to ethanol tolerancebetween C and e-C, between C and Ti (isogenic ETS), andbetween C and e-Ti (Ti challenged with ethanol), andrevealed significant variation in gene activities depending onthe comparison set and sampling timepoint. The resultsof these and other studies and the present study aresummarized in Table II. Ma and Liu (2010b) also showedthat all 34 genes of e-C overlapped with e-Ti and six genes(HSP31, IRC15, ADH1, ADH2, ADH3, and ADH7) werecommon between Ti and e-Ti. These data imply that ethanolchallenge induces a similar set of genes regardless whether astrain is ethanol tolerant or not, and that the expressionprofile of an unchallenged ETS is considerably differentfrom that of challenged ETS. We propose that ethanol

tolerance should be dealt with separately from ethanolinduction. In fact, PUT1, ATH1, and NTH1, whichconfer ethanol tolerance when deleted or disrupted(Supplementary Table 2), were up-regulated upon ethanolinduction (Ma and Liu, 2010b): sixfold in e-C and fivefold ine-Ti for PUT1; 2.2-fold in e-Ti for ATH1; 2.0-fold in e-C and2.7-fold in e-Ti for NTH1. Among the genes constitutivelyup-regulated in four ETSs (SR4-3, Y50316, ETS2, andETS3), only three genes (CTT1, HSP12, and SPI1) werecommon between SR4-3, ETS2, and ETS3. Considering themethods employed for developing the strains used for eachassay (i.e., breeding for SR4-3, adaptation evolutionaryengineering for Y50316, and gTME for ETS2 and ETS3),ethanol tolerance may be achieved by several independentroutes in S. cerevisiae.

When the construction of a strain with enhanced highglucose and ethanol tolerance by exploiting gTME wasreported (Alper et al., 2006), this technique seemed to be apromising approach to directly reveal multiple stresstolerance. Such genetic traits were claimed to be conferredby a specific SPT15 mutant allele (SPT15-300), whichresulted from reprogramming of the global gene expression.However, no follow-up studies have been reported, andneither ethanol nor high glucose tolerance trait was observedwhen cells containing the SPT15-300 allele were grown onrich media (Baerends et al., 2009). In the present study, fiveethanol-tolerant S. cerevisiae strains were constructed byexploiting gTME. The ethanol tolerance phenotype wassustained when cells were grown on YPD agar (Fig. 5A). Thisdiscrepancy may be due to differential expression of a set of

Table II. Comparison sets and strategies used to identify ethanol tolerance-related genes by comparing expression profiles.

Set

Strategy used

Number of

regulated genesa

SourceControl Counterpart Up Down

C e-C

NSb e-NSb Microarray 200–400 NA Alexandre et al. (2001); Chandler et al. (2004);

Dinh et al. (2009); Hirasawa et al. (2007);

Marks et al. (2008); Rossignol et al. (2003);

Varela et al. (2005); Wu et al. (2006)

Y50049 e-Y50049 qRT-PCRc 34d 50d Ma and Liu (2010b)

C Ti

K701 SR4-3 Filter screening 6 NA Ogawa et al. (2000)

Y50049 Y50316 qRT-PCRc 12d 5d Ma and Liu (2010b)

L3262 ETS2 Microarray 45 (34e) 11(8e) This study

L3262 ETS3 Microarray 79 (34e) 21(8e) This study

C e-Ti

Y50049 e-Y50316 qRT-PCRc 41d 16d Ma and Liu (2010b)

e-C e-Tu

X2180-1A e-K9 Microarray 283f 167f Shobayashi et al. (2007)

The prefix ‘e’ represents ethanol challenge. The subscripts indicate that the counterpart is isogenic (i) or unrelated (u) to control. Strains used are inparentheses. C, control strain; T, ethanol-tolerant strain; NA, not available.

aBased on twofold change.bNot specified here due to the variety.cPerformed for 175 genes selected from previous studies for an ethanol-tolerant yeast and its parental strain.dShowing twofold change at any timepoint during 48-h-long ethanol challenge.eCommon between ETS2 and ETS3.fRegulated under either shaking or static condition.



genes induced by different SPT15 alleles (SPT15-300 andSPT15-M2 or -M3) as shown in the DNA microarrayanalysis. Most notably, genes involved in the amino acidmetabolism including leucine, the elevation of which hasbeen suspected to closely associated with ethanol toleranceconferred by SPT15-300 (Baerends et al., 2009), were not up-regulated by SPT15-M2 or -M3 (Table I). The differentialexpression cannot be simply explained by the difference inlocation of point mutations: three of SPT15-300 (F177S,Y195H, and K218R) clustered in the repeat element 2 (Alperet al., 2006), whereas those of SPT15-M1–5 scattered on theSPT15 ORF without overlapping with each other, includingthe non-conserved N-terminal region of 60 amino acids(Fig. 2). Even a truncated SPT15 (SPT15-M1) was formed.However, it should be noted that an amino acid change(s)was commonly found in the repeat element 2 of SPT15-M1–5, suggesting that this domain might be related with ethanoltolerance observed in this study. It would be interesting todetermine which amino acids are responsible for ethanoltolerance by reverting mutations to their wild types orshuffling mutations between SPT15-M1–5.

We also showed that the enhanced ethanol toleranceconferred by gTME through mutated SPT15 alleles resultedin 25% increase of ethanol production (Fig. 6). Previously,the effect of enhanced ethanol tolerance generated in variousways such as genomic shotgun (Hong et al., 2010), SGKOscreening (Teixeira et al., 2009), genome shuffling (Hou,2009) and transcription factor overexpression (Hou et al.,2009), was examined by measuring the highest ethanol titerfrom batch cultures. In these studies, however, the ethanolproduction was increased by slightly more than 10%compared to the control strains. The contrasting increase inethanol production between the previous and presentstudies may be due to different fermentation conditions:most probably, flask culture versus bioreactor culture.Although it is difficult to compare the efficiency of severaltechnologies mentioned above, gTME seems to be anefficient tool to create strains with enhanced ethanoltolerance. In addition, the SPT15 mutation libraryconstructed in this study may be further used for screeningstrains with enhanced tolerance to other stresses such asheat, fermentation inhibitors, osmotic pressure, and so on.

We are grateful to Dr. Won-Kee Hur (Seoul National University,

Korea) for providing S. cerevisiae BY4741 deletion mutant library and

to Drs. J. B. Park (Ewha Womans University, Korea) and Y. C. Park

(Kukmin University, Korea) for helpful comments especially in

fermentation. This research was supported by Pioneer Research

Center Program through the National Research Foundation of Korea

funded by Ministry of Education, Science and Technology (No. 2009-

0081512 and No. 2007-2005047).

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